code: def cli_main():
      parser = ArgumentParser()
      parser.add_argument(
          "--checkpoint-path",
          type=pathlib.Path,
          help="Path to checkpoint to use for evaluation.",
          required=True,
      )
      parser.add_argument(
          "--global-stats-path",
          default=pathlib.Path("global_stats.json"),
          type=pathlib.Path,
          help="Path to JSON file containing feature means and stddevs.",
      )
      parser.add_argument(
          "--librispeech-path",
          type=pathlib.Path,
          help="Path to LibriSpeech datasets.",
          required=True,
      )
      parser.add_argument(
          "--sp-model-path",
          type=pathlib.Path,
          help="Path to SentencePiece model.",
          required=True,
      )
      parser.add_argument(
          "--use-cuda",
          action="store_true",
          default=False,
          help="Run using CUDA.",
      )
      args = parser.parse_args()
      run_eval(args)
  
file_path: audio/examples/asr/librispeech_conformer_rnnt/eval.py
imports: import logging
  import pathlib
  from argparse import ArgumentParser
  import sentencepiece
  import torch
  import torchaudio
  from lightning import ConformerRNNTModule
  from transforms import get_data_module
label_desc: Use image node_id 3 for calling a global function with example usage: cli_main() without return types